AI Fluency Education Lead

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

Anthropic is seeking an AI Fluency Education Lead to create courses and content that teach people how AI works and how to work well with AI. Most people right now pick up AI wherever they happen to find it: a prompt from a coworker, a video promising ten hacks, or a screenshot from LinkedIn. It’s hard to discern which tidbits are short term tactics and what skills will be enduring. AI Fluency is our work to close that gap: teaching how AI actually works, and how to work well alongside it, so people can make their own decisions and judgements with AI instead of copying someone else’s. Note that this does not cover product training. We recognize that most people do not use a single tool or single model, so  AI Fluency is deliberately model agnostic. We teach durable mindsets and understandings that help someone use AI well and safely, no matter what system is in front of them.

Much of this role is about creation: writing, filming, prototyping, and publishing. It’s also about building the systems that let that work multiply and reach the right audiences. We can’t teach every audience ourselves, so you’d design a modular library — short videos, exercises, frameworks, one-pagers, all free and openly licensed — along with the AI-assisted pipelines that remix and assemble those pieces into something specific for a given learner. You will also work with other teams to decide which audiences we go after, which topics we prioritize, and which formats we pursue. You may also invent formats that don’t exist yet, because most AI education still looks like an online course from 2015 and we don’t think the subject and the medium should be that far apart.

You would work closely with a sister group on the education team that researches what fluency means and how to measure it. You’re the person who takes that and turns it into something someone can actually learn from.

Key responsibilities

• Own the curriculum for general-public AI fluency end to end — the roadmap, the sequencing, the quality bar, and the call on what we teach and what we deliberately leave out.

• Curate and create the AI fluency material itself — curricula, courses, videos, essays, exercises, interactive lessons — and set the quality bar for any partner content creation engagements

• Build AI-assisted production pipelines so the distance from an idea to a published piece keeps getting shorter while the quality keeps going up
• Turn research frameworks into material that resonates for people whose jobs look nothing like ours: nurses, teachers, small business owners, policymakers, community leaders, and so on
• Learn from and co-create with outside institutions, such as educators, public-sector organizations, and community groups
• Prototype learning formats that only work with AI in the loop — personalized paths, conversational practice, assessment that adapts to the learner — and get rough versions in front of real people in days rather than quarters
• Measure whether the teaching worked — completion is not comprehension, and comprehension is not changed behavior. Define what learning actually looks like for this audience and instrument for it.

You may be a good fit if you have

• Deep experience designing content and curricula for adult learners at significant scale, with real taste for what makes learning stick when you’re not in the room.
• Exceptional writing for general audiences, and specifically the knack for turning a technical idea into a mental model that’s accurate and also intuitive to novices and those who have never seen it before
• Experience making multimedia learning content end to end — scripts, video, interactive — and working with agencies and partners to deliver on multiple projects in short deadlines
• A working practice of using Claude and other LLMs as infrastructure in your own production
• Enough technical comfort to build light tooling and automations yourself; this isn’t an engineering role, but you shouldn’t be intimidated by adding to the pipeline that produces your work
• Experience-derived opinions about pedagogy you’ll argue for,…